Computers are often used to solve complex quantitative and qualitative problems. For problems that involve a large data set, a specially trained professional, known as a data scientist, may be hired. The data scientist interprets the data set and constructs models that can be processed by computers to solve the problem. However, hiring data scientists is cost prohibitive for many organizations.
For certain types of problems, advanced machine learning techniques may be available to develop a model, such as a neural network, that is comparable in accuracy to a model that would be created by a data scientist. However, such machine learning techniques can require a large number of iterations to converge on an acceptable neural network, and as a result, can use significant computing resources to generate and train a neural network.